Descriptive summary of fatal work-related injuries, Western States, 2011-2017.

Work-related deaths are a persistent occupational health issue that can be prevented. However, prevention opportunities can be hampered by a lack of adequate public health resources. The Western States Occupational Network (WestON) is a network of federal, state, and local occupational health professionals that includes a 19-state region of the United States. To encourage public health collaboration, WestON partners examined work-related fatalities within the region. Fatality counts (numerators) were obtained from the U.S. Bureau of Labor Statistics (BLS) Census of Fatal Occupational Injuries restricted-access research files for all workers ages ≥15 years and fatally injured in WestON states from 2011 through 2017. Estimates of full-time equivalent hours worked (FTE) (denominators) were retrieved from the BLS Current Population Survey. Annual average fatality rates were calculated as number of fatalities per 100,000 FTE over the study period. Rates were stratified by state, select demographics, industry sector, and event/exposure types. Pearson chi-squared tests and rate ratios with 95% confidence probability limits were used to assess rate differences. All analyses were conducted using SAS v.9.4. From 2011 through 2017, the annual average overall occupational fatality rate for the WestON region was 3.5 fatalities per 100,000 FTE, comparable to the overall U.S. fatality rate. Male workers had a fatality rate almost 10 times higher than female workers in the region. Fatality rates increased with successive age groups. Alaska and New Mexico had significantly higher fatality rates for all racial/ethnic groups compared to respective regional rates. Wyoming, North Dakota, and Montana had the three highest occupational fatality rates among foreign-born workers. Agriculture/forestry/fishing, mining/oil/gas extraction, and transportation/warehousing/utilities were industry sector groups with the three highest fatality rates regionally. Transportation-related incidents were the most frequent event type associated with occupational fatalities for all 19 states. Work-related fatalities are a crosscutting occupational public health priority. This analysis can be an impetus for collaborative multistate initiatives among a dynamic and varied occupational public health network to better meet the needs of a rapidly changing workforce.

Adding industry and occupation questions to the behavioral risk factor surveillance system: new opportunities in public health surveillance.

OBJECTIVES: Industry and occupation variables are overlooked in many public health surveillance efforts, yet they are useful for describing the burden and distribution of various public health diseases, behaviors, and conditions. This study is the first ever analysis of the Colorado Behavioral Risk Factor Surveillance System (BRFSS) to describe chronic conditions and risk behaviors by occupation. It is intended to provide a new perspective on this existing data source and demonstrate the value of occupation as a core demographic variable for public health research, policy, and practice. METHODS: Two standardized employment questions were included in the 2012 Colorado BRFSS survey and administered to eligible survey respondents who were employed, self-employed, or out of work for less than one year. Occupation data were coded using the National Institute for Occupational Safety and Health (NIOSH) Industry and Occupation Computerized Coding System. We analyzed health behaviors and conditions by major occupation groups. We calculated prevalence estimates and 95% confidence intervals (CIs). RESULTS: The prevalence of chronic conditions, health statuses, and risk behaviors (e.g., smoking and seatbelt use) varied significantly by occupation. For example, compared with all workers (93.6%, 95% CI 92.7, 94.5), significantly fewer workers in farming, forestry, fishing and construction, extraction jobs (87.0%, 95% CI 82.0, 92.0) reported always or nearly always wearing a seatbelt while driving. Additionally, significantly more office and administrative support workers (27.5%, 95% CI 22.5, 32.4) compared with all workers (20.6%, 95% CI 19.3, 22.0) were obese. Further observation and research is needed to understand the effects of occupation on health outcomes and behaviors. CONCLUSION: There are no other Colorado state-level datasets that link health behaviors and chronic conditions with occupation. This study shows that the prevalence of chronic conditions and risk behaviors varies substantially by occupation. Other states conducting the BRFSS may choose to adopt the NIOSH industry and occupation module and add other questions to further investigate health issues by occupation.